Estimated Birth Weight by current Weight-and Age During the First Five Days of Life

In the developing countries, measurement of birth weight is subjected to methodological problems. The main issue is the difficulty of measuring birth weight soon after delivery. Two relevant questions are proposed by this study : 1) can a birth weight be estimated several hours or days after a baby was delivered ?, and 2) can an estimated birth weight be collected by paramedical personnel with reliable results? To answer these questions, we conducted a study at Dr. Sardjito Hospital, Yogyakana, to evaluate agreement between two paramedical personnel in the routine measurements of neonatal weight in the rooming-in ward. The behavior of these two paramedical personnel was observed from one month when they examined 32 neonates. Both of them weighed the neonate at 7.00 hours and one weighed the neonate at 15.00 or 21.00 hours. The order of the last two measurements was made alternatingly. This resulted in 156 pairs of measurement for agreement analysis. There was a strong evidence that the two raters have almost perfect agreement on measuring neonatal weights (intraclass correlation coefficient = 0.978). The second part of this study looked at neonatal weight during the first five days of life. The neonatal weights were measured three times a day up to age of the days. We constructed a formula for estimating their birth weight based on a current neonatal weight and age in days. Birth weight can be estimated using formula : Birth weight ; 51 + 1. 029 x current weight - 10 x age in days. The data fitted very well to this least square estimate with a coefficient of determination (R) = 0.95.

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URGENSI AUDIT JUDGEMENT PADA POST CLEARANCE AUDIT

JURNAL PERSPEKTIF BEA DAN CUKAI ◽

10.31092/jpbc.v4i1.760 ◽

2020 ◽

Vol 4 (1) ◽

Author(s):

Masruri Muchtar ◽

Prasetya Utama

Keyword(s):

Self Efficacy ◽

Least Square ◽

Coefficient Of Determination ◽

Experience Level ◽

Level Of Education ◽

Future Studies ◽

Ordinary Least Square ◽

Audit Judgment ◽

Depth Interview ◽

Study Results

ABSTRACT:The auditor should have eminence audit judgment to support their assignment This research aims to provide empirical evidence that self-efficacy, experience, level of education, and skepticism have an impact on audit judgment. The population are auditors who had carried out post-clearance audit assignments. This research uses a quantitative approach by testing the theories and hypotheses that have been prepared. Ordinary least square (OLS) linear regression as an analytical model is used in this study. Results show that experience and education level have no impact on audit judgment, whereas self-efficacy and skepticism have a positive and significant impact on audit judgment. Efforts to improve self-efficacy and auditor skepticism are urgently needed. The coefficient of determination describes the variation of variables of self-efficacy, experience, level of education, and skepticism able to explain the variation of audit judgment variables by 51%. The remaining 49% is explained by other variables not involved in this study. Future studies may enhance with other variables and employ in-depth interview methods.Keywords: audit judgment, experience, level of education, post-clearance audit, self-efficacy, skepticism, post-clearance audit ABSTRAK:Auditor seyogyanya memiliki kemampuan audit judgment yang berkualitas guna mendukung penugasannya. Tujuan penelitian adalah memberikan bukti empiris bahwa efikasi diri, pengalaman, tingkat pendidikan, dan skeptisisme memiliki pengaruh terhadap audit judgement. Populasi dalam penelitian ini adalah auditor Direktorat Jenderal Bea dan Cukai (DJBC) yang pernah melakukan post clearance audit. Ini merupakan pendekatan kuantitatif yang menguji teori serta hipotesis yang telah disusun. Riset ini menggunakan regresi linear ordinary least square (OLS) sebagai model analisis. Hasil studi memperlihatkan pengalaman dan tingkat pendidikan tidak berpengaruh pada audit judgement, namun efikasi diri dan skeptisisme berpengaruh signifikan pada audit judgement. Implikasinya DJBC perlu memberikan perhatian khusus terhadap berbagai upaya dalam peningkatan efikasi diri dan skeptisisme auditor. Tulisan ini adalah pengembangan beberapa penelitian sebelumnya namun dalam konteks pengujian untuk jenis audit ketaatan. Nilai koefisien determinasi menggambarkan variasi variabel efikasi diri, pengalaman, tingkat pendidikan, dan skeptisisme dapat menjelaskan variasi variabel audit judgement sebesar 51%. Sisanya sebesar 49% dijelaskan oleh variabel lainnya yang tidak diujikan dalam tulisan ini. Dengan adanya keterbatasan waktu pada penelitian ini diharapkan mendorong penelitian berikutnya untuk dapat menyertakan beberapa variabel lain yang relevan dan melengkapinya dengan metode in-depth interview.Kata Kunci: bea dan cukai, efikasi diri, pengalaman, skeptisisme, tingkat pendidikan

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Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽

10.3390/foods10040885 ◽

2021 ◽

Vol 10 (4) ◽

pp. 885

Author(s):

Sergio Ghidini ◽

Luca Maria Chiesa ◽

Sara Panseri ◽

Maria Olga Varrà ◽

Adriana Ianieri ◽

...

Keyword(s):

Root Mean Square ◽

Near Infrared ◽

Nir Spectroscopy ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Coefficient Of Determination ◽

Mean Square ◽

Tuna Fish ◽

Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

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Influence factor of consumers interest on using E-money

International Journal of Social Sciences and Humanities ◽

10.29332/ijssh.v3n2.311 ◽

2019 ◽

Vol 3 (2) ◽

pp. 176-186

Author(s):

Ni Wayan Mentari ◽

I Nyoman Djinar Setiawina ◽

I Made Kembar Sri Budhi ◽

I Wayan Sudirman

Keyword(s):

Influence Factor ◽

Consumer Attitudes ◽

Structural Equations ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Consumer Knowledge ◽

Perceived Benefits ◽

Consumer Interest ◽

The Relationship

The objectives of this study was to determine the factors that influence consumer interest in using e-money in Badung and Denpasar City in Bali. This study uses the analysis of SEM structural equations with alternative Partial Least Square (PLS). Consumer attitudes mediate the influence of the relationship between perceived benefits and perceived ease of consumer interest in using e-money, the attitude of consumers in using e-money does not mediate the effect of the relationship between customer knowledge on consumer interest in using e-money. The coefficient of determination R-square for attitude variables is 0.502, which means that the variable attitude of consumers in using e-money can be explained by the variable perception of benefits, perceived convenience and consumer knowledge by 50.2 percent, or in other words, every variant of consumer attitudes e-money will be explained by the variable perception of benefits, perceived ease and consumers knowledge by 50.2 percent, the rest explained by other variables outside the model by 49.8 percent.

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Application of FTIR Spectroscopy and Chemometrics for Halal Authentication of Beef Meatball Adulterated with Dog Meat

Indonesian Journal of Chemistry ◽

10.22146/ijc.27159 ◽

2018 ◽

Vol 18 (2) ◽

pp. 376 ◽

Cited By ~ 2

Author(s):

Wiranti Sri Rahayu ◽

Abdul Rohman ◽

Sudibyo Martono ◽

Sudjadi Sudjadi

Keyword(s):

Ftir Spectroscopy ◽

Reliable Method ◽

Cross Validation ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Calibration Model ◽

Mean Square ◽

Folch Method ◽

Halal Authentication

Beef meatball is one of the favorite meat-based food products among Indonesian community. Currently, beef is very expensive in Indonesian market compared to other common meat types such as chicken and lamb. This situation has intrigued some unethical meatball producers to replace or adulterate beef with lower priced-meat like dog meat. The objective of this study was to evaluate the capability of FTIR spectroscopy combined with chemometrics for identification and quantification of dog meat (DM) in beef meatball (BM). Meatball samples were prepared by adding DM into BM ingredients in the range of 0–100% wt/wt and were subjected to extraction using Folch method. Lipid extracts obtained from the samples were scanned using FTIR spectrophotometer at 4000–650 cm-1. Partial least square (PLS) calibration was used to quantify DM in the meatball. The results showed that combined frequency regions of 1782–1623 cm-1 and 1485-659 cm-1 using detrending treatment gave optimum prediction of DM in BM. Coefficient of determination (R2) for correlation between the actual value of DM and FTIR predicted value was 0.993 in calibration model and 0.995 in validation model. The root mean square error of calibration (RMSEC) and standard error of cross validation (SECV) were 1.63% and 2.68%, respectively. FTIR spectroscopy combined with multivariate analysis can serve as an accurate and reliable method for analysis of DM in meatball.

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Authentication of Patin Fish Oil (Pangasius micronemus) using FTIR Spectroscopy Combined with Chemometrics

Indonesian Journal of Chemometrics and Pharmaceutical Analysis ◽

10.22146/ijcpa.487 ◽

2020 ◽

pp. 23

Author(s):

Anggita Rosiana Putri ◽

Abdul Rohman ◽

Sugeng Riyanto ◽

Widiastuti Setyaningsih

Keyword(s):

Root Mean Square Error ◽

Fish Oil ◽

Ftir Spectroscopy ◽

Mean Square Error ◽

Root Mean Square ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Coefficient Of Determination ◽

Mean Square

Authentication of Patin fish oil (MIP) is essential to prevent adulteration practice, to ensure quality, nutritional value, and product safety. The purpose of this study is to apply the FTIR spectroscopy combined with chemometrics for MIP authentication. The chemometrics method consists of principal component regression (PCR) and partial least square regression (PLSR). PCR and PLSR were used for multivariate calibration, while for grouping the samples using discriminant analysis (DA) method. In this study, corn oil (MJ) was used as an adulterate. Twenty-one mixed samples of MIP and MJ were prepared with the adulterate concentration range of 0-50%. The best authentication model was obtained using the PLSR technique using the first derivative of FTIR spectra at a wavelength of 650-3432 cm-1. The coefficient of determination (R2) for calibration and validation was obtained 0.9995 and 1.0000, respectively. The value of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.397 and 0.189. This study found that the DA method can group the samples with an accuracy of 99.92%.

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The Effects of Social Capital on Performance of Coffee-Based Agribusiness Smes in Tabanan Regency, Bali Province, Indonesia

The International Journal of Social Sciences and Humanities Invention ◽

10.18535/ijsshi/v6i6.05 ◽

2019 ◽

Vol 6 (6) ◽

pp. 5513-5520

Author(s):

Ida Ayu Komang Juniasih ◽

Dr. I Wayan Widnyana ◽

I Gusti Agung Ayu Ambarawati ◽

Dwi Putra Darmawan

Keyword(s):

Social Capital ◽

Small And Medium Enterprises ◽

Local Area ◽

Sem Analysis ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Business Success ◽

P Values ◽

Significance Level

Small and Medium Enterprises (SMEs) is one of the businesses that have an important role in the country's economy. The potential of these SMEs needs to get serious attention from the local government in order to increase the potential of the local area in supporting the economy. Several SMEs have been developed in Tabanan Regency considering local potential-based agribusiness, namely coffee processing agribusiness, especially Robusta coffee. The development of SMEs does not only require financial capital but also requires social capital. The purpose of this study was to analyze the effect of social capital on the performance of coffee-based agribusinessSMEs in Tabanan Regency, Bali Province.The social capital in thisstudy includes trust, norms and networks, Sampling was taken by using Solvin technique from the members of 16 SMEs, counting to 73 respondents. The location of the study was conducted by purposive sampling. The data used were qualitative and quantitative data and analyzed by using Partial Least Square (PLS) - SEM analysis. The result shows that the construct of trust had an effect on the performance of SMEs of coffee-based agribusinesses of 0.482 (48.2 per cent) with the level of significance of p values < 0.05. The construct of norms affected the performance of SMEsby 0.326 (32.6 per cent)with the significance level of p values < 0.05. The network construct influenced the performance of SMEsby 0.287 or 28.7 per cent with the significance level (p values < 0.05). The results of combined analysis show that social capital consisting of trust, norms, and networks on the performance of coffee-based agribusiness SMEshad a coefficient of determination (R-square) of 0.448, reflecting the effect is categorized moderate.In this study it shows that social capital consisting of trust, norms, and networks had a positive and significant effect on the performance of coffee-based agribusinessSMEs in Tabanan Regency. There needs to be strengthening of social capital from both SME players and government officials for business developmenttogether with other capital to achieve business success.

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192 Effects of dam relative calving date on progeny performance

Journal of Animal Science ◽

10.1093/jas/skz258.054 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 27-28

Author(s):

Vitor R G Mercadante ◽

Robin R White ◽

John Currin ◽

Heather L Bradford ◽

Sherrie Clarke ◽

...

Keyword(s):

Birth Weight ◽

Fixed Effects ◽

Least Square ◽

Mixed Effect ◽

Full Dataset ◽

Effect Model ◽

Calving Season ◽

Cattle Herds ◽

Virginia Department ◽

Significant Interaction Term

Abstract The objective of this study was to establish the relationships between when a cow was born within the calving season and the performance of her offspring. Data from the Virginia Department of Corrections beef cattle herds were collated for 7 locations over 7 years (2010 to 2017), with 2 calving seasons per year. Data from Spring of 2011 were missing. The full dataset contained 19,253 individual animal observations. Within each location, year, and calving season combination, the calving season was defined as starting when the first calf was born and terminating when the final calf was born. The relative calving date (RCD) within each calving season was defined by calculating the number of days between when the calving occurred and when the calving season started, divided by the length of the season in days. For heifer calves that were retained as replacement heifers (n = 2,800), the RCD and birth weight of their calves were used as response variables of a mixed-effect model with fixed effects of dam RCD, season (fall vs spring), and calf sex. All 2 and 3 way interactions were also included as fixed effects. Both calving year and sire were used as random effects. Fixed effects were iteratively removed from the model when non-significant; however, non-significant linear terms were retained if involved in a significant interaction term. The final calf RCD model included significant effects of dam RCD (P = 0.006), season (P < 0.001), calf sex (P = 0.0737), and the interaction between dam RCD and calf sex (P = 0.055). The final calf birth weight model included only linear terms for calf sex (P < 0.001) and dam RCD (P = 0.029). Least square means for these relationships are depicted in Table 1.

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Application of FTIR Spectroscopy and HPLC Combined with Multivariate Calibration for Analysis of Xanthones in Mangosteen Extracts

Scientia Pharmaceutica ◽

10.3390/scipharm88030035 ◽

2020 ◽

Vol 88 (3) ◽

pp. 35

Author(s):

Endjang Prebawa Tejamukti ◽

Widiastuti Setyaningsih ◽

Irnawati ◽

Budiman Yasir ◽

Gemini Alam ◽

...

Keyword(s):

Quantitative Analysis ◽

Multivariate Calibration ◽

Principal Component Regression ◽

Principal Component ◽

Ethanolic Extract ◽

Ftir Spectra ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Garcinia Mangostana

Mangosteen, or Garcinia mangostana L., has merged as an emerging fruit to be investigated due to its active compounds, especially xanthone derivatives such as α -mangostin (AM), γ-mangostin (GM), and gartanin (GT). These compounds had been reported to exert some pharmacological activities, such as antioxidant and anti-inflammatory, therefore, the development of an analytical method capable of quantifying these compounds should be investigated. The aim of this study was to determine the correlation between FTIR spectra and HPLC chromatogram, combined with chemometrics for quantitative analysis of ethanolic extract of mangosteen. The ethanolic extract of mangosteen pericarp was prepared using the maceration technique, and the obtained extract was subjected to measurement using instruments of FTIR spectrophotometer at wavenumbers of 4000–650 cm−1 and HPLC, using a PDA detector at 281 nm. The data acquired were subjected to chemometrics analysis of partial least square (PLS) and principal component regression (PCR). The result showed that the wavenumber regions of 3700–2700 cm−1 offered a reliable method for quantitative analysis of GM with coefficient of determination (R2) 0.9573 in calibration and 0.8134 in validation models, along with RMSEC value of 0.0487% and RMSEP value 0.120%. FTIR spectra using the second derivatives at wavenumber 3700–663 cm−1 with coefficient of determination (R2) >0.99 in calibration and validation models, along with the lowest RMSEC value and RMSEP value, were used for quantitative analysis of GT and AM, respectively. It can be concluded that FTIR spectra combined with multivariate are accurate and precise for the analysis of xanthones.

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Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy

ISRN Soil Science ◽

10.1155/2013/720589 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 9

Author(s):

Tadele Amare ◽

Christian Hergarten ◽

Hans Hurni ◽

Bettina Wolfgramm ◽

Birru Yitaferu ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Diffuse Reflectance ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Coefficient Of Determination ◽

Calibration Models ◽

The Stability

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used. The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9), Maybar (84. 0.57, 2.5), Megech (85, 0.15, 2.6), and Wondo Genet (86, 0.52, 2.7) indicating that the models were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

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Evaluating the Spectral Indices Efficiency to Quantify Daytime Surface Anthropogenic Heat Island Intensity: An Intercontinental Methodology

Remote Sensing ◽

10.3390/rs12172854 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2854 ◽

Cited By ~ 1

Author(s):

Mohammad Karimi Firozjaei ◽

Solmaz Fathololoumi ◽

Naeim Mijani ◽

Majid Kiavarz ◽

Salman Qureshi ◽

...

Keyword(s):

Los Angeles ◽

Surface Temperature ◽

Feature Space ◽

Least Square ◽

Anthropogenic Heat ◽

Coefficient Of Determination ◽

Landsat 8 ◽

Heat Island ◽

Spectral Indices ◽

Spatial Coverage

The surface anthropogenic heat island (SAHI) phenomenon is one of the most important environmental concerns in urban areas. SAHIs play a significant role in quality of urban life. Hence, the quantification of SAHI intensity (SAHII) is of great importance. The impervious surface cover (ISC) can well reflect the degree and extent of anthropogenic activities in an area. Various actual ISC (AISC) datasets are available for different regions of the world. However, the temporal and spatial coverage of available and accessible AISC datasets is limited. This study was aimed to evaluate the spectral indices efficiency to daytime SAHII (DSAHII) quantification. Consequently, 14 cities including Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome in Europe and Dallas, Seattle, Minneapolis, Los Angeles, Chicago, and Phoenix in the USA, were selected. A set of 91 Landsat 8 images, the Landsat provisional surface temperature product, the High Resolution Imperviousness Layer (HRIL), and the National Land Cover Database (NLCD) imperviousness data were used as the AISC datasets for the selected cities. The spectral index-based ISC (SIISC) and land surface temperature (LST) were modelled from the Landsat 8 images. Then, a linear least square model (LLSM) obtained from the LST-AISC feature space was applied to quantify the actual SAHII of the selected cities. Finally, the SAHII of the selected cities was modelled based on the LST-SIISC feature space-derived LLSM. Finally, the values of the coefficient of determination (R2) and the root mean square error (RMSE) between the actual and modelled SAHII were calculated to evaluate and compare the performance of different spectral indices in SAHII quantification. The performance of the spectral indices used in the built LST-SIISC feature space for SAHII quantification differed. The index-based built-up index (IBI) (R2 = 0.98, RMSE = 0.34 °C) and albedo (0.76, 1.39 °C) performed the best and worst performance in SAHII quantification, respectively. Our results indicate that the LST-SIISC feature space is very useful and effective for SAHII quantification. The advantages of the spectral indices used in SAHII quantification include (1) synchronization with the recording of thermal data, (2) simplicity, (3) low cost, (4) accessibility under different spatial and temporal conditions, and (5) scalability.

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